Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems

@article{Melnyk2016SemiMarkovSV,
  title={Semi-Markov Switching Vector Autoregressive Model-Based Anomaly Detection in Aviation Systems},
  author={Igor Melnyk and Bryan L. Matthews and Hamed Valizadegan and Arindam Banerjee and Nikunj C. Oza},
  journal={Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining},
  year={2016}
}
  • Igor MelnykB. Matthews N. Oza
  • Published 21 February 2016
  • Computer Science
  • Proceedings of the 22nd ACM SIGKDD International Conference on Knowledge Discovery and Data Mining
In this work we consider the problem of anomaly detection in heterogeneous, multivariate, variable-length time series datasets. Our focus is on the aviation safety domain, where data objects are flights and time series are sensor readings and pilot switches. In this context the goal is to detect anomalous flight segments, due to mechanical, environmental, or human factors in order to identifying operationally significant events and highlight potential safety risks. For this purpose, we propose… 
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54 Citations
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